IDENTIFICATION OF THE DYNAMICS OF A MOVING OBJECT WITH THE USE OF NEURAL NETWORKS
Yu. N. Zolotukhin, K. Yu. Kotov, A. M. Svitova, E. D. Semenyuk, M. A. Sobolev
Institute of Automation and Electrometry, Siberian Branch, Russian Academy of Sciences, pr. Akademika Koptyuga 1, Novosibirsk, 630090 Russia
Keywords: идентификация динамики, квадрокоптер, расширенный фильтр Калмана, рекуррентная нейронная сеть Элмана, identification of the dynamics, quadrotor, extended Kalman filter, Elman recurrent neural network
Abstract
A method for identification of the dynamics of a quadrotor-type vehicle is proposed. The method is based on the Elman recurrent neural network, which corresponds to the canonical form of a dynamic system in the space of states and does not require structural correction. The results of a numerical experiment reveal the convergence of the network learning algorithm with the use of an extended Kalman filter
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